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Hui Li

4 papers hereh-index 121.5k citations16 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author3
  • middle author1

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • cs.CV4
same name
  • Hui Li — 62 papers, h 49
  • Hui Li — 19 papers
  • Hui Li — 13 papers, h 20
  • Hui Li — 11 papers, h 14
  • Hui Li — 10 papers, h 11
  • Hui Li — 7 papers

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20172020
most citedTowards End-to-End Car License Plates Detection and Recognition with Deep Neural Networks

40 citations · 69 across the 3 of their papers we have counts for

collaborators

4 papers

cs.CV2020★ 1 cited

Give Me Something to Eat: Referring Expression Comprehension with Commonsense Knowledge

Peng Wang, Dongyang Liu, Hui Li +1

Conventional referring expression comprehension (REF) assumes people to query something from an image by describing its visual appearance and spatial location, but in practice, we…

cs.CV2018

Visual Question Answering as Reading Comprehension

Hui Li, Peng Wang, Chunhua Shen +1

Visual question answering (VQA) demands simultaneous comprehension of both the image visual content and natural language questions. In some cases, the reasoning needs the help of c…

cs.CV2017★ 40 cited

Towards End-to-End Car License Plates Detection and Recognition with Deep Neural Networks

Hui Li, Peng Wang, Chunhua Shen

In this work, we tackle the problem of car license plate detection and recognition in natural scene images. We propose a unified deep neural network which can localize license plat…

cs.CV2017★ 28 cited

Towards End-to-end Text Spotting with Convolutional Recurrent Neural Networks

Hui Li, Peng Wang, Chunhua Shen

In this work, we jointly address the problem of text detection and recognition in natural scene images based on convolutional recurrent neural networks. We propose a unified networ…

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